On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery

Polarimetric SAR images are a rich data source for crop mapping. However, quad-pol sensors have some limitations due to their complexity, increased data rate, and reduced coverage and revisit time. The main objective of this study was to evaluate the added value of quad-pol data in a multi-temporal...

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Autores: Larrañaga Urien, Arantzazu, Álvarez-Mozos, Jesús
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Recursos:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/22499
Acesso em linha:https://hdl.handle.net/2454/22499
Access Level:acceso abierto
Palavra-chave:RADARSAT-2
Polarimetric features
Separability
Random forests
Crop classification
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spelling On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imageryLarrañaga Urien, ArantzazuÁlvarez-Mozos, JesúsRADARSAT-2Polarimetric featuresSeparabilityRandom forestsCrop classificationPolarimetric SAR images are a rich data source for crop mapping. However, quad-pol sensors have some limitations due to their complexity, increased data rate, and reduced coverage and revisit time. The main objective of this study was to evaluate the added value of quad-pol data in a multi-temporal crop classification framework based on SAR imagery. With this aim, three RADARSAT-2 scenes were acquired between May and June 2010. Once we analyzed the separability and the descriptive analysis of the features, an object-based supervised classification was performed using the Random Forests classification algorithm. Classification results obtained with dual-pol (VV-VH) data as input were compared to those using quad-pol data in different polarization bases (linear H-V, circular, and linear 45º), and also to configurations where several polarimetric features (Pauli and Cloude–Pottier decomposition features and co-pol coherence and phase difference) were added. Dual-pol data obtained satisfactory results, equal to those obtained with quad-pol data (in H-V basis) in terms of overall accuracy (0.79) and Kappa values (0.69). Quad-pol data in circular and linear 45º bases resulted in lower accuracies. The inclusion of polarimetric features, particularly co-pol coherence and phase difference, resulted in enhanced classification accuracies with an overall accuracy of 0.86 and Kappa of 0.79 in the best case, when all the polarimetric features were added. Improvements were also observed in the identification of some particular crops, but major crops like cereals, rapeseed, and sunflower already achieved a satisfactory accuracy with the VV-VH dual-pol configuration and obtained only minor improvements. Therefore, it can be concluded that C-band VV-VH dual-pol data is almost ready to be used operationally for crop mapping as long as at least three acquisitions in dates reflecting key growth stages representing typical phenology differences of the present crops are available. In the near future, issues regarding the classification of crops with small field sizes and heterogeneous cover (i.e., fallow and grasslands) need to be tackled to make this application fully operational.MDPIProyectos e Ingeniería RuralLanda Ingeniaritza eta Proiektuak2016info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2454/22499reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad Pública de NavarraInglés© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) licensehttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:academica-e.unavarra.es:2454/224992026-06-17T12:41:47Z
dc.title.none.fl_str_mv On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
title On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
spellingShingle On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
Larrañaga Urien, Arantzazu
RADARSAT-2
Polarimetric features
Separability
Random forests
Crop classification
title_short On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
title_full On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
title_fullStr On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
title_full_unstemmed On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
title_sort On the added value of quad-pol data in a multi-temporal crop classification framework based on RADARSAT-2 imagery
dc.creator.none.fl_str_mv Larrañaga Urien, Arantzazu
Álvarez-Mozos, Jesús
author Larrañaga Urien, Arantzazu
author_facet Larrañaga Urien, Arantzazu
Álvarez-Mozos, Jesús
author_role author
author2 Álvarez-Mozos, Jesús
author2_role author
dc.contributor.none.fl_str_mv Proyectos e Ingeniería Rural
Landa Ingeniaritza eta Proiektuak
dc.subject.none.fl_str_mv RADARSAT-2
Polarimetric features
Separability
Random forests
Crop classification
topic RADARSAT-2
Polarimetric features
Separability
Random forests
Crop classification
description Polarimetric SAR images are a rich data source for crop mapping. However, quad-pol sensors have some limitations due to their complexity, increased data rate, and reduced coverage and revisit time. The main objective of this study was to evaluate the added value of quad-pol data in a multi-temporal crop classification framework based on SAR imagery. With this aim, three RADARSAT-2 scenes were acquired between May and June 2010. Once we analyzed the separability and the descriptive analysis of the features, an object-based supervised classification was performed using the Random Forests classification algorithm. Classification results obtained with dual-pol (VV-VH) data as input were compared to those using quad-pol data in different polarization bases (linear H-V, circular, and linear 45º), and also to configurations where several polarimetric features (Pauli and Cloude–Pottier decomposition features and co-pol coherence and phase difference) were added. Dual-pol data obtained satisfactory results, equal to those obtained with quad-pol data (in H-V basis) in terms of overall accuracy (0.79) and Kappa values (0.69). Quad-pol data in circular and linear 45º bases resulted in lower accuracies. The inclusion of polarimetric features, particularly co-pol coherence and phase difference, resulted in enhanced classification accuracies with an overall accuracy of 0.86 and Kappa of 0.79 in the best case, when all the polarimetric features were added. Improvements were also observed in the identification of some particular crops, but major crops like cereals, rapeseed, and sunflower already achieved a satisfactory accuracy with the VV-VH dual-pol configuration and obtained only minor improvements. Therefore, it can be concluded that C-band VV-VH dual-pol data is almost ready to be used operationally for crop mapping as long as at least three acquisitions in dates reflecting key growth stages representing typical phenology differences of the present crops are available. In the near future, issues regarding the classification of crops with small field sizes and heterogeneous cover (i.e., fallow and grasslands) need to be tackled to make this application fully operational.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/22499
url https://hdl.handle.net/2454/22499
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
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repository.mail.fl_str_mv
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